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TKNearestNeighbors Members Published Properties
Published Properties
 
Name 
Description 
 
Total number of attributes.  
 
Total number of discrete valued attributes or fields holding discreting values in the dataset.  
 
Defines the distance model used, when calculating the distance between examples.  
 
Total number of learned examples.  
 
Total number of real valued attributes or fields holding real values in the dataset.  
 
Set to True, if Class indexes are zero based.  
 
Defines the K parameter for the K-NN algorithm.  
 
Set the value of this property to the index of the example that you want to be ignored during the classification.  
 
Specifies the value indicating a "missing value" (no entry) for discrete attributes in the dataset.  
 
Specifies the value indicating a "missing value" (no entry) for real valued attributes in the dataset.  
 
If true, the number of attributes compared will be normalized between comparisons.  
 
Set this property to true, to store all learned examples.  
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